Thank you david 😊
most of my query looks like:
{
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"range": {
"timestamp": {
"from": 1403567280,
"to": 1403567340,
"include_lower": true,
"include_upper": false
}
}
}
},
"facets" : {
"val": {
"statistical": {
"field": "val"
}
}
}
}
Sent from Surface
From: David Pilato
Sent: Friday, August 1, 2014 10:43 AM
To: [email protected]
Well. I guess it depends on your query. What does it look like?
--
David ;-)
Twitter : @dadoonet / @elasticsearchfr / @scrutmydocs
Le 1 août 2014 à 04:14, "Wang Yong" <[email protected]> a écrit :
Hi folks, I have an index storing lots of time serial data. The data are put
into index by :
curl -XPUT 'localhost:9200/testindex/action1/1?pretty' -d '
{
"val": 23,
"timestamp": 1406822400
}'
And the only thing I search in this index is histogram facet in a very short
time range, like “recent 5 min”. I found that the performance was pretty good
at first. But when the index get bigger, the performance dropped to
unacceptable. I found the IO maybe the bottleneck by checking the result of
iostat.
My question is, even I only facet in a very short time range, why the size of
index has so big impact on the performance of such query? Do I have to use
daily index, just like logstash?
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